compute_hindcast(hind, verif, metric='pearson_r', comparison='e2o', dim='init', max_dof=False, add_attrs=True, **metric_kwargs)¶
Verify hindcast predictions against verification data.
- hind (xarray object) – Hindcast ensemble.
Expected to follow package conventions:
init: dim of initialization dates *
lead: dim of lead time from those initializations Additional dims can be member, lat, lon, depth, …
- verif (xarray object) – Verification data with some temporal overlap with the hindcast.
- metric (str) – Metric used in comparing the decadal prediction ensemble with the
verification data. (see
- comparison (str) –
How to compare the decadal prediction ensemble to the verification data:
- e2o : ensemble mean to verification data (Default)
- m2o : each member to the verification data
- dim (str or list) – dimension to apply metric over. default: ‘init’
- max_dof (bool) –
If True, maximize the degrees of freedom by slicing
verifto a common time frame at each lead.
If False (default), then slice to a common time frame prior to computing metric. This philosophy follows the thought that each lead should be based on the same set of initializations.
- add_attrs (bool) – write climpred compute args to attrs. default: True
- metric_kwargs (**) – additional keywords to be passed to metric (see the arguments required for a given metric in Metrics).
Predictability with main dimension
skill (xarray object)
- hind (xarray object) – Hindcast ensemble. Expected to follow package conventions: *